SemML: Reusable ML for condition monitoring in discrete manufacturing

Machine learning (ML) is gaining much attention for data analysis in manufacturing. Despite the success, there is still a number of challenges in widening the scope of ML adoption. The main challenges include the exhausting effort of data integration and lacking of generalisability of developed ML pipelines to diverse data variants, sources, and domain processes. In this demo we present our SemML system that addresses these challenges by enhancing machine learning with semantic technologies: by capturing domain and ML knowledge in ontologies and ontology templates and automating various ML steps using reasoning. During the demo the attendees will experience three cunningly-designed scenarios based on real industrial applications of manufacturing condition monitoring at Bosch, and witness the power of ontologies and templates in enabling reusable ML pipelines

Improving the reliability of locomotives by implementation of the operation of RAMS means and methods

В статье рассмотрена возможность управления надежностью локомотивов путем внедрения комплексной системы RAMS. Применение одного из инструментов FRACAS, используемого в системе RAMS позволяет создать базу знаний, которая обеспечит формирование полной, объективной структурированной информации о неисправностях, отказах и событиях, связанных с возникновением отказов.The article considers the possibility of controlling the reliability of locomotives by introducing an integrated system RAMS. The use of one of the FRACAS means used in the RAMS system allows you to create a knowledge base that will ensure the formation of complete, objective, structured information about faults, failures and events associated with the occurrence of failures

Updating DL-Lite ontologies through first-order queries

In this paper we study instance-level update in DL-LiteA, the description logic underlying the OWL 2 QL standard. In particular we focus on formula-based approaches to ABox insertion and deletion. We show that DL-LiteA, which is well-known for enjoying first-order rewritability of query answering, enjoys a first-order rewritability property also for updates. That is, every update can be reformulated into a set of insertion and deletion instructions computable through a nonrecursive datalog program. Such a program is readily translatable into a first-order query over the ABox considered as a database, and hence into SQL. By exploiting this result, we implement an update component for DLLiteA-based systems and perform some experiments showing that the approach works in practice.Peer ReviewedPostprint (author's final draft